@inproceedings{27dc7052899f40ae80e68b0bd39c8fdc,
title = "REVRANK: A Fully Unsupervised Algorithm for Selecting the Most Helpful Book Reviews",
abstract = "We present an algorithm for automatically ranking user-generated book reviews according to review helpfulness. Given a collection of reviews, our REVRANK algorithm identifies a lexicon of dominant terms that constitutes the core of a virtual optimal review. This lexicon defines a feature vector representation. Reviews are then converted to this representation and ranked according to their distance from a 'virtual core' review vector. The algorithm is fully unsupervised and thus avoids costly and error-prone manual training annotations. Our experiments show that REVRANK clearly outperforms a baseline imitating the Amazon user vote review ranking system.",
author = "Oren Tsur and Ari Rappoport",
note = "Publisher Copyright: Copyright {\textcopyright} 2009, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 3rd International AAAI Conference on Weblogs and Social Media, ICWSM 2009 ; Conference date: 17-05-2009 Through 20-05-2009",
year = "2009",
month = may,
day = "20",
doi = "10.1609/icwsm.v3i1.13945",
language = "English",
series = "Proceedings of the 3rd International AAAI Conference on Weblogs and Social Media, ICWSM 2009",
publisher = "AAAI press",
pages = "154--161",
booktitle = "Proceedings of the 3rd International AAAI Conference on Weblogs and Social Media, ICWSM 2009",
}